Assessment of Blood Glucose and Electrolytes during Cardiopulmonary Bypass in Diabetic and Non-Diabetic Patients of Pakistan
Bibliographic record
Abstract
INTRODUCTION: Perioperative hyperglycemia has been shown to be related to higher levels of morbidity and mortality in patients on cardiopulmonary bypass (CPB) undergoing coronary artery bypass grafting (CABG), both diabetic and non-diabetic. Blood electrolytes, like sodium, potassium, calcium, and chloride play a very important role in the normal functioning of the body and can lead to a variety of clinical disorders if they become deficient. A minimal number of studies have been conducted on the simultaneous perioperative changes in both blood glucose and electrolyte levels during CPB in Pakistan. Therefore, our aim is to record and compare the changes in blood glucose and electrolyte levels during CPB in diabetic and non-diabetic patients. MATERIALS & METHODS: This was a prospective, observational study conducted on 200 patients who underwent CABG with CPB, from October 2014 to March 2015. The patients were recruited from the Cardiac Surgery Ward, Civil Hospital Karachi after they complied with the inclusion criteria. Repeated-measures analysis of variance (ANOVA) was used to compare the trend of the changes perioperatively for the two groups. RESULTS: There was no significant difference in changes in blood glucose between the two groups (P = 0.62). The only significant difference detected between the two groups was for PaCO2 (P = 0.001). Besides, further analysis revealed insignificant group differences for the trend changes in other blood electrolytes (P > 0.05). CONCLUSION: Our findings highlighted that there is no significant difference in blood electrolytes changes and the increase in blood glucose levels between diabetic and non-diabetic patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".